Marginalising posterior covariance matrix with application to Bayesian operational modal analysis

Consider making Bayesian inference of vector-valued model parameters {x,y} based on observed data D. When the ‘posterior’ (i.e., given data) probability density function (PDF) of {x,y} has a centralised shape, it can be approximated in the spirit of Laplace integral asymptotics by a Gaussian PDF cen...

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Bibliographic Details
Main Author: Au, Siu-Kui
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2024
Subjects:
Online Access:https://hdl.handle.net/10356/180891
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Institution: Nanyang Technological University
Language: English

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